How can I extract characters from a binary image when I have its centroid?

Question

Kartik Bharadwaj 2017-9-22

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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/357955-how-can-i-extract-characters-from-a-binary-image-when-i-have-its-centroid

评论： Image Analyst 2017-10-7

采纳的回答： Image Analyst

在 MATLAB Online 中打开

I = imread('download5.png');

J = rgb2gray(I);

K = bwareaopen(J,10,8);

h1 = fspecial('gaussian', 3, 1);

h2 = fspecial('average', 2);

g = imfilter(K,h1, 'replicate');

g1 = imfilter(g,h2, 'replicate');

g1 = ~g1;

g1 = bwmorph(g1,'clean');

g1 = bwmorph(g1,'bridge',Inf);

g1 = imdilate(g1, [1 1 1; 1 1 1; 1 1 1]);

[B, L, N, A] = bwboundaries(g1, 'holes');

s = regionprops(L,'all');

imshow(g1)

hold on

for k = 1:length(B)

    boundary = B{k};
    if k <= N
        plot(boundary(:,2), boundary(:,1))
    end

end

centroids = cat(1, s.Centroid);

plot(centroids(:,1),centroids(:,2), 'b*')

In the above image, I am getting extra centroids apart from that of the characters. How can I eliminate the unwanted centroids and extract only the characters using centroids? (Extract meaning that I want to save each character separately as an image)

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Answer 1

Image Analyst 2017-9-22

1
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/357955-how-can-i-extract-characters-from-a-binary-image-when-i-have-its-centroid#answer_282727

See my Image Segmentation Tutorial http://www.mathworks.com/matlabcentral/fileexchange/?term=authorid%3A31862&sort=downloads_desc It shows you how to find blobs and then crop out the blobs to individual images by asking reginoprops() for the BoundingBox.

As far as removing "unwanted" blobs, you'll have to define what unwanted is. If it's just small ones, then you can use bwareafilt() or bwareaopen().

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Kartik Bharadwaj 2017-10-7

Neither am I. However, to satiate my curiosity on whether we can smoothen the edges, I want to try it out.

Image Analyst 2017-10-7

savitzky_golay_filter_smooth_outline.m

There are a variety of ways to smooth a binary image, such as blurring and thresholding, or calling imclose(), or using sgolayfilt() or other means, such as the attached demo.

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